Diagnostics monitor of the braking efficiency in the on board diagnostics system for the motor vehicles

Gajek, Andrzej

doi:10.1088/1757-899x/148/1/012038

Cited by 3 publications

(1 citation statement)

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“…As the dependence of the response to the imposition of the braking process on the quantity that forces this process, the dependence of the braking deceleration (response to the excitation) on the pressure in the braking system (the quantity which forces braking) was selected. The paper [7] confirms the possibility of its determination in vehicle operation conditions and its use for current diagnostics of the braking system of a motor vehicle. This relationship directly influences the technical condition of the hydraulic braking system in the Skoda Octavia research vehicle.…”

Section: The Model Formulationsupporting

confidence: 65%

The use of artificial intelligence methods in the analysis of the results of vehicle braking deceleration tests in the diagnostics of the braking system of a motor vehicle

Dobaj

2022

tren

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The article presents the concept of using an artificial neural network to approximate the parameters describing the vehicle braking process, from the point of view of the application of this method in the diagnostics of the braking system. The artificial neural network of non-linear autoregression was used to approximate the dependence of the braking deceleration and the pressure in the braking system. The effectiveness of the neural network was checked depending on the number of neurons in its hidden layer and on the applied learning algorithm. The operation of the neural network was verified based on the actual braking processes of the Skoda Octavia, carried out with different dynamics, with different car weights and different tire inflation pressures. After verifying the neural network, it was used to approximate the braking deceleration values for the pressure values exceeding those present in the input data set. This action allows the analysis of the possibility of the vehicle obtaining a braking deceleration, which qualifies its braking system as efficient. Two concepts of using a neural network to solve this problem were analyzed. Conclusions related to the validity of the development of the discussed methods were drawn.

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Section: The Model Formulationsupporting

confidence: 65%